Neal Ramaswamy
I’m a Computer Science student passionate about understanding the fundamental principles that make intelligent systems work to drive benefit for humanity.
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My Path
My professional journey began at Tesla, where I spent several years working in Facilities Engineering and Production Engineering. During my time there, I gained valuable experience in:
- Data Engineering: Building ETL processes and data pipelines using Python and SQL
- Manufacturing Analytics: Implementing statistical process control and yield optimization
- Computer Vision: Troubleshooting and improving production line vision systems
- Process Optimization: Leading projects that improved line throughput by up to 41%
- Reliability: Developing predictive maintenance programs for mechanical and electrical equipment to enhance reliability and reduce probabilistic downtime
The more I worked with data and automation systems, the more I wanted to understand the theoretical underpinnings of how machines can learn and make intelligent decisions.
Academic Pursuit
This curiosity led me to pursue a Master’s in Computer Science & Engineering at the University of Nevada, Reno, where I’m currently maintaining a 4.0 GPA. My academic interest is on:
- Path Planning: Studying algorithms and mathematical methods for navigation and decision-making in intelligent systems
- Control Theory: Exploring feedback systems and control mechanisms that enable robust and adaptive AI behavior
- Mathematics Behind Modern AI Architectures: Delving into the mathematical foundations that underpin contemporary neural networks and machine learning models